The strategic partnership between AVEVA and IFS was formed around a simple yet ambitious aim: to enable operators to run their entire asset lifecycle as a single process. Over its working life, an asset cycles through design, construction, operation, upkeep, and reinvestment many times, but most organizations still manage each of these stages with its own systems, teams, and budgets. When information is passed from one stage to the next, much of its context is lost along the way, leaving operators to make critical decisions with only part of the picture. 

Now the first major pillar of our partnership is here, enabling operators to unlock the art of the possible. Continuous Asset Decision Intelligence (CADI) combines AVEVA’s operational and engineering intelligence with IFS’ enterprise execution, capital planning, and AI orchestration. The joint solution powers maintenance, investment, and execution decisions across the integrated asset lifecycle with real-time operational and asset data, enabling operators to base investment decisions on timely and accurate data, rather than guesswork. 

Siloed systems delay time-to-action 

Many asset owners needing to maintain and upgrade legacy assets are currently flying blind. The data they need to make timely and accurate decisions is often simply not there, or it arrives far too late – delayed en route from sensor to spreadsheet.  

As a result, operators end up investing too heavily in assets that don’t need it, or underinvesting in those that do. Seasoned employees who know their assets inside and out can mitigate some of this damage by applying their expertise and knowledge, but with many due to retire soon, taking their knowledge with them, a longer-term solution is needed. 

Sharpening investment decisions with CADI 

CADI from AVEVA and IFS addressed these challenges, eliminating friction in the decision-making process and enabling operators to work from a single asset plan. The joint solution unlocks three immediate value adds: 

  1. Condition-to-Capital. Capital plans can be re-ranked continuously by live asset health data, not annually by spreadsheet. Operators are thereby able to preserve capital flexibility and avoid overcommitting funds while being able to analyze capital-efficiency impact in near real time. 
  1. Condition-to-Work-Order. Asset anomalies trigger predictive, context-rich work orders in a matter of hours. The solution increases the first-time-fix rate, reduces response times, and ensures that institutional knowledge is embedded in the enterprise systems. 
  1. Investment Defense. Every capital dollar can be traced from the risk that justified it to the reliability it produced. As a result, prudency challenge risk falls and benefits can be quantified in clear data rather than anecdotes. 

Proven Industrial AI 

CADI is extended across AVEVA & IFS’s asset lifecycle solutions. Its insights are confidence scored by AI, helping the board make those crucial investment decisions. In addition, engineers are supported by leading-edge agentic execution, with digital “workers” detecting undocumented failure modes and drafting FMECA updates for engineer review.  

CADI can also predict and prescribe, providing data on probability of failure and the associated consequences along with a confidence score. Finally, AI agents provide explainable recommendations at the point of work, helping technicians complete tasks rapidly and at the first time of asking. 

By bringing together OT intelligence, enterprise execution, and capital planning in one loop, AVEVA and IFS are unlocking the art of the possible and enabling operators to connect data and insights in powerful new ways, from sensor to boardroom. CADI provides what operators need most: the operational context and enterprise AI they need to decide what work to do, when to do it, and whether to repair, defer or replace.  

With greater real-time visibility into how their assets are performing, operators are also better placed to understand energy efficiency and carbon across their operations, supporting more informed sustainability decisions and helping them do more with less.